FGAF-CDG: fuzzy geographic routing protocol based on compressive data gathering in wireless sensor networks

Abstract

In the wireless sensor networks (WSNs), energy consumption is one of the significant factors. Most of the energy in a WSN is consumed by communication between nodes. To minimize energy consumption, routing protocols can be merged with data aggregation techniques. The geographic adaptive fidelity (GAF) protocol is one of the prominent geographic routing protocols which is proposed in order to reduce energy consumption in WSNs. Moreover, compressive sensing (CS) theory presented as an alternative method for data gathering in WSNs, known as compressive data gathering (CDG). CDG reduces the cost of communications and balances the energy load in the network without imposing heavy computation or transmission overhead. With CDG, instead of receiving all readings from the sensors, the sink may receive few weighted sums of all the readings by which original data can be recovered by the sink. In this paper, we propose a GAF-based routing protocol based on CDG technique named fuzzy GAF based on CDG (FGAF-CDG). In this work, we partition the sensors area into virtual hexagonal grid cells firstly and then we lay the cells according to their geographic locations. In each sampling round, cluster head (CH) sensor in each grid cell is selected based on a fuzzy logic-based algorithm. Then, CH readings will be forwarded to the sink in a multi-hop path based on a fuzzy-based routing algorithm in the CDG form. Simulation results show that the proposed method results in superior efficiency as compared to other competitive GAF-based methods. For example, the proposed model offers about 50% reduction in energy consumption as compared to FTGAF-HEX method depending on the dimensions of the sensors area.